Shared Ontology for AI & Digital Systems
A Common Language for a Digital World
The digital economy is fragmented by incompatible data definitions, siloed systems, and inconsistent standards. The WDG Shared Ontology offers a unifying foundation — a globally accessible vocabulary for data, systems, and governance. Designed to be adopted across nations, sectors, and platforms, it enables interoperability, transparency, and trust.
What Is Ontology in Digital Governance?
An ontology is more than a glossary — it's a structured framework of concepts, entities, and relationships that define how digital systems understand and interact with the world.
In the context of digital governance and AI, this ontology provides:
Key Domains and Taxonomy
The ontology spans core areas such as:
Identity
Persons, credentials, identity providers
- Digital identity verification and authentication systems
- Credential management and validation frameworks
- Identity provider standards and interoperability
Access & Consent
Permissions, authentication, usage rights
- Granular permission management systems
- Consent tracking and withdrawal mechanisms
- Usage rights and licensing frameworks
Digital Rights
Privacy, fairness, algorithmic accountability
- Privacy protection and data subject rights
- Algorithmic fairness and bias prevention
- Accountability mechanisms for automated decisions
Governance
Nations, agencies, regulatory instruments
- National digital governance frameworks
- Regulatory compliance and oversight mechanisms
- International cooperation and standards alignment
Infrastructure
Devices, protocols, platforms
- Digital infrastructure standards and protocols
- Platform interoperability requirements
- Device security and management frameworks
Data
Types, sources, sensitivity, classification
- Data classification and sensitivity labeling
- Source attribution and lineage tracking
- Data quality and validation standards
Intelligence Systems
Models, inference, bias types
- AI model documentation and metadata standards
- Inference transparency and explainability
- Bias detection and mitigation frameworks
Each concept is categorized into standardized taxonomies, tagged for machine-readability and human alignment.
How to Use This Ontology
AI Teams
As a starter kit for AI teams building responsible models
- Standardized vocabulary for AI model documentation
- Common frameworks for bias detection and mitigation
- Shared understanding of ethical AI principles
Data Harmonization
To harmonize data schemas across institutions, ministries, or product lines
- Unified data models and schema standards
- Cross-institutional data sharing protocols
- Consistent metadata and classification systems
Government Alignment
For governments to align national digital policies with international standards
- Policy framework templates and guidelines
- International standard compliance mapping
- Cross-border cooperation mechanisms
Education
In education, to teach common digital governance concepts
- Standardized curriculum and learning materials
- Common terminology and concept definitions
- Assessment frameworks for digital literacy
System Auditing
To audit existing systems for consistency and ethical alignment
- Audit checklists and evaluation criteria
- Compliance assessment frameworks
- Gap analysis and remediation guidance
This ontology is designed for versioning, extension, and collaborative governance.
Start Using the Ontology
Access the Shared Ontology
Open structured ontology file or interactive browser
Adopt for Your Systems
Guide or form to begin integration, map your data models, or join implementation calls
Suggest an Extension
Optional CTA to expand or localize the ontology